North America Thematic Maps
This week’s assignment will encompass the following concepts covered in Class 4 lecture & lab:
Specific techniques covered this week will include:
Note: the map example layout applies to both the primary and extra credit options of the assignment, while the map theme itself is applicable to the extra credit component of the assignment.
The Class 4 quiz (02/19/2023 - Sunday) will features 10 questions covering content in the textbook Chapter 4 and Chapter 5 as noted below:
Supplemental readings: SQL cheatsheet (Not necessary for Class 4 assignment; good for general reference) Normalizing Census Data Normalizing Census Data Formulas
Below are links to further readings for those interested in the United States political dimension of ‘MAUP’, Gerrymandering and a divided US electorate:
For this assignment submission, utilize the data process from the Class 4 Demonstration Lab to get started.
General concepts covered in Class 4 Assignment - Thematic Mapping with US Census Data :
.gdbNote: this week will feature a
CRS‘on the fly projection’ transformation to achieve a better map ‘shape’ for the required assignment map. The image below shows an equal area projection vs. the defaultWGS84projection. The image source is linked to an article that discusses these differences further:
Map Project Options Suitable for US Contiguous States
Source: https://source.opennews.org/articles/choosing-right-map-projection/
In this assignment, one thematic map for Contiguous United States
based on a demographic variable derived from the American Community
Survey 2020 data ACS_2020_5YR_County (5-year estimates from
the 2016-2020 ACS) will be developed. This will require a two-step
process: access and prepare the data, followed by a classified mapping
of the data.
The top grade for this map will be 90 points. There is an extra credit component for the additional 10 points. The video guide towards end of assignment will guide you through an example for the extra credit component using the age+sex table.
Note: the video features older ACS data, but the process will be very similar to load, connect and map census data.
The videos will not cover the cartographic design elements covered in previous classes; make sure to use all the cartography skills you learned to enhance this week’s deliverable - legend, inserts (consider including Alaska and Hawaii and Puerto Rico as map inserts - an example HERE), map titling and data sourcing. Scale bars and north arrows are often not essential for effective thematic mapping- use them sparingly, if at all, when producing thematic maps.
Note: including map insets for Hawaii, Alaska, Puerto Rico and other county census geographies not in the lower 48 is not required of this assignment - only if you prefer to add them to your map layout.
Navigate to data and download bundled product
TIGER/Line with Selected Demographic and Economic Data via
the following link:
US Census ACS .gdb product
Utilize
American Community Survey 5-Year Estimates — Geodatabase Format 2016-2020
Select County > Download Data:
Download Census Data
ACS_2020_5YR_COUNTY.gdb.zip. make sure to keep the
resulting directory with folder extension intact:
ACS_2020_5YR_COUNTY.gdb:.gdb are available for import into QGIS.
However, we only need the geometry for the county boundaries plus one
theme - for this mapping, we will use the Total Population from
the Age and Sex theme.Note that this is an estimate of the total population, but for our purposes a good approximation. The census derives total population estimates within the ACS product via a process known as Imputation.
With population counts secured, we will then derive a population density estimate per county in the final mapping. This process is Normalization by Geography; that is, we are using population counts and normalizing those by county areal size. This is a different normalization process than Normalization by Population inside a census theme.
We need to know which table to import. To do this, we utilize an online html document - ACS variables 2020 that lists all the acs tables and their themes. There are over 64,000 variables in this dataset, so isolating the correct table is an essential first step.
ACS Variables and their Concepts listed via API
source: https://api.census.gov/data/2020/acs/acs5/variables.html
Alternatively, we can import the COUNTY_METADATA_2020
tabular data and view within QGIS.
COUNTY_METADATA_2020
For the assignment mapping, we will use the
SEX BY AGE table B01001. Here we will use just
the first variable, which is the total population estimate per county -
B01001e1:
B01001e1|SEX BY AGE - Universe: Total population - Total: -- (Estimate)Census Theme in QGIS Attribute Table
.gdb to
begin mapping. We will discuss the .gdb format during Class
4 Lecture and Lab. Further, see video references at end of assignment
for .gdb imports to QGIS.Point QGIS to the .gdb
Select both the geometry and table B01001 -
SEX BY AGE. This is also referred to as the
X01_AGE_AND_SEX table:
Select Geometry + Tabular Data
Connect to .gdb - feature + tabular
data
AGE AND SEX
will be exported as .csv outward from the .gdb
structure. As this is done, the table will be ‘thinned’ to the just
those variables needed for the mapping - the OBJECTID,
GEOID and B01001_001E alone. Save the export
as acs.2020.population.csv into the assignment project
folder directory. Also state No geometry as geometry
type:
10. Next, import
acs.2020.population.csv
as delimited text:
Delimited Text as import file type
ALAND
variable in the dataset which equates to square meters for each county.
To calculate area units - ALAND as Square Miles - the
following calculation is used:1 sq. mile = 2,589,988.110336 metersALAND/2589988.110336.gdb to a .shp and title
acs.geo.shp. Make sure NOT to change the coordinate system
which is NAD83 - EPSG:4269:.shp Export
sq.mile within the
acs.geo.shp, not the tabular data.Field Calculator
Next, a table join will be enacted between the
geometry acs.geo and the tabular data
acs.2020.population. As is, these two data files exist
side-by-side in the QGIS project. We need to ‘join’ these two files
based on a common attribute. This is known as a ‘table join’. To
start, save the project to update to the current data
files.
Next, preview the two attribute tables to
determine the attribute join. In this case both contain the critical
GEOID that is the US Census unique identifier across all
census geographies:
Table Join Preparation
asc.geo = GEOID_DATATable Join Preparation
asc.2020.population = GEOIDasc.geo, navigate to
Properties > Joins > green plus button and populate as
follows:Table Join Preparation
asc.2020.population now joined
correctly to the asc.geo layer (far right field in image
below). This table join is currently loaded in temporary memory. It must
now be exported as a new .shp before proceeding:Table Join Preparation
acs.2.map.shp:.shp Export
.shp Export
.shp Export - Result
acs.2.map.shp feature. Create a new
field via the Field Calculator and populate as follows.
Proceed to Toogle editing OFF and save the new
field:Population Density Calculation in Field Calculator
Note: a Whole Number (integer) field type is selected as persons can only be whole numbers, not decimal numbers, i.e. there are only whole persons, not partial persons. There are approximately 30 counties that contain less than 1 person per sq. mile. These counties will simply receive a
0and will be classed accordingly in the final thematic map.
pop.den > Classify button at
bottom:Graduated Symbology - Equal Count - Quantile
22. Rerun the classification using
quantile method, results in a much more ‘balanced’ map
across the 5 breaks, while still retaining the low population
geographies of the Natural Breaks method:
Graduated Symbology - Natural Breaks
Cartographic Result
North America Albers Equal Area Conic. This will give the
final map better areal representation - an ingredient that is important
for choropleth mapping:Transform the project CRS
Better areal representation with Albers CRS projection
Produce final Map layout and design. Output as PDF 300 DPI 8.5”x11”
or 11”x17” (use .png or .tiff if PDF at 300
DPI produces too large file size export). If pursuing the extra map II,
follow the guidelines provided below, and again, produce map layout,
design and output similar to the main map assignment.
You are strongly encouraged to pursue the extra credit portion of the assignment for a top potential score of 100 points. While the required map above will feature basic demographic data at the county level, the extra credit map will feature a more tailored exploration of census data. In this extra credit mapping, you will utilize the same data source bundled US Census ACS product. Instead of normalizing the data by areal units (population density per sq. miles), you will normalize the census theme by the theme universe population per US county.
The equation for this population normalization:
census theme count/census universe population*100
Like the main assignment, you can utilize the bundled
.gdb format for the 2020
version of the ACS 5-year survey.
Assignment 4 Extra Credit - Thematic Mapping - normalization + classification methods:
Note: the video guide uses ACS of a prior vintage. This should not impact generally the methdology of the assignment shown in the video.
US Census Links:
Online tools & utilities to aid thematic map design:
Helpful articles and resources for census data and thematic mapping techniques:
Case Study - The Marshall Project:
The Marshall Project extracted the number of adults in correctional facilities per county from the 2000, 2010 and 2020 Decennial Census.
U.S. County distribution of Incarcerated Populations
Data Fields in the Dataset